• Journal of Environmental Health Sciences
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• v.31 no.5 s.86
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• pp.431-443
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• 2005

This study was performed to investigate the perceptions of the opinion leaders, such as government officials, researchers, NGO workers, and journalists on the risks of endocrine disrupters (EDs) and genetically modified organisms (GMOs) as well as the related policies on these two hazards or potential hazards. The opinion leaders generally considered the EDs as the most serious hazard among twenty-one environmental health hazards in Korea, and agreed that the EDs would continuously be the most serious hazard. On overall average, the GMOs were ranked the 11th among the twenty-one health hazards. Further investigation indicated that the GMOs were variously ranked by the group of respondents: they were ranked the 2nd by the NGO workers, the 7th by the journalists, the 9th by the researchers and the 11th by the government officials. In general, the respondents considered the dioxin as a hazard with the highest risk while the GMOs were considered less hazardous. The opinion leaders considered that although the risks of the GMOs and EDs were not fully verified, the risks should be controlled through the legislation. The EDs and GMOs should be separately regulated for the time being, while the EDs should put under more strengthened regulation. It is recommended that a web-site containing the information on the EDs and the GMOs be prepared for the journalists. In addition, a training program in relation to the EDs and the GMOs needs to be organized by the Korean Press Foundation and the Korea Food and Drug Administration to educate the journalists. A committee consisting of government officials, scientists, and NGO workers needs to be established, and it should provide framework of future policies and public relations programs.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.199-219
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• 2018

With the everyday use of the Internet and the spread of various smart devices, users have been able to communicate in real time and the existing communication style has changed. Due to the change of the information subject by the Internet, data became more massive and caused the very large information called big data. These Big Data are seen as a new opportunity to understand social issues. In particular, text mining explores patterns using unstructured text data to find meaningful information. Since text data exists in various places such as newspaper, book, and web, the amount of data is very diverse and large, so it is suitable for understanding social reality. In recent years, there has been an increasing number of attempts to analyze texts from web such as SNS and blogs where the public can communicate freely. It is recognized as a useful method to grasp public opinion immediately so it can be used for political, social and cultural issue research. Text mining has received much attention in order to investigate the public's reputation for candidates, and to predict the voting rate instead of the polling. This is because many people question the credibility of the survey. Also, People tend to refuse or reveal their real intention when they are asked to respond to the poll. This study collected comments from the largest Internet portal site in Korea and conducted research on the 19th Korean presidential election in 2017. We collected 226,447 comments from April 29, 2017 to May 7, 2017, which includes the prohibition period of public opinion polls just prior to the presidential election day. We analyzed frequencies, associative emotional words, topic emotions, and candidate voting rates. By frequency analysis, we identified the words that are the most important issues per day. Particularly, according to the result of the presidential debate, it was seen that the candidate who became an issue was located at the top of the frequency analysis. By the analysis of associative emotional words, we were able to identify issues most relevant to each candidate. The topic emotion analysis was used to identify each candidate's topic and to express the emotions of the public on the topics. Finally, we estimated the voting rate by combining the volume of comments and sentiment score. By doing above, we explored the issues for each candidate and predicted the voting rate. The analysis showed that news comments is an effective tool for tracking the issue of presidential candidates and for predicting the voting rate. Particularly, this study showed issues per day and quantitative index for sentiment. Also it predicted voting rate for each candidate and precisely matched the ranking of the top five candidates. Each candidate will be able to objectively grasp public opinion and reflect it to the election strategy. Candidates can use positive issues more actively on election strategies, and try to correct negative issues. Particularly, candidates should be aware that they can get severe damage to their reputation if they face a moral problem. Voters can objectively look at issues and public opinion about each candidate and make more informed decisions when voting. If they refer to the results of this study before voting, they will be able to see the opinions of the public from the Big Data, and vote for a candidate with a more objective perspective. If the candidates have a campaign with reference to Big Data Analysis, the public will be more active on the web, recognizing that their wants are being reflected. The way of expressing their political views can be done in various web places. This can contribute to the act of political participation by the people.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.9
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• pp.530-538
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• 2002

In this paper, we propose a new caching strategy for web servers. The proposed algorithm collects on]y the statistics of the requested file, for example the popularity, when a request arrives. And, at times, only files with higher popularity are cached all together. Because the cache remains unchanged until the cache is made newly, web server can use very efficient data structure for cache to determine whether a file is in the cache or not. This increases greatly tile efficiency of cache manipulation. Furthermore, the experiment that is performed with real log files built by web servers shows that the cache hit ratio and the cache hit ratio are better than those produced by LRU. The proposed algorithm has a drawback such that the cache hit ratio may decrease when the popularity of files that is not in the cache explodes instantaneously. But in our opinion, such explosion happens infrequently, and it is easy to implement the web servers to adapt them to such unusual cases.

• The Journal of the Korea Contents Association
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• v.16 no.9
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• pp.751-768
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• 2016

The success of the journey to the west of tvN's shows the positive prospect of web entertainment. This study highlights how viewers actively select web progrmas and how they diffuse the infomrmation of web programs to explore the possibility of success of web program and the change of viewing environment. This study revealed the attention of viewers affected the diffusion of programs via social media. The highness of the viewer's attention cause the highness of active interaction between users. The production company of web entertaninment has to focus on the high hits strategy. In the view of journalists, they covered on the appearance of the heroin rather than the content of the program. The relationship of viewing type and viral type via SNS is related with the activity of viewers. If viewers participate in viewing they express their opinion on the web entertainment actively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.1
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• pp.109-118
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• 2016

Traffic congestions are rapidly increasing in urban areas. In order to reduce these problems, it needs real-time data and intelligent techniques to quickly identify traffic activities with useful information. This paper proposes a Fuzzy Domain Ontology(FDO)-based opinion mining system to monitor the transportation network in real-time as well to make a city polarity map for travelers. The proposed system retrieves tweets and reviews related to transportation activities and a city. The feature opinions are extracted from these tweets and reviews and then used FDO to identify transportation and city features polarity. This FDO and intelligent prototype are developed using $Prot{\acute{e}}g{\acute{e}}$ OWL (Web Ontology Language) and JAVA, respectively. The experimental result shows satisfactory improvement in tweets and review's analyzing and opinion mining.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.2
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• pp.75-95
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• 2022

This study was carried out with the aim of analyzing the development and functional changes of Webdewey, which has become a basic tool of classification learning, analyzing it in terms of usability for learners, and suggesting specific ways to improve WebDewey's usability. In order to achieve this research objective, the concepts and principles of UI and usability were first laid out, and Webdewey's structure and key functions were analyzed. Since then, Webdewey's media changes and periodical feature changes have been analyzed. In addition, an opinion survey was conducted on the usability of WebDewey among learners who used WebDewey in the learning process, and proposed ways to improve WebDewey's usability based on the implications and direction of improvement derived from it. In terms of UI, proposals have been made to introduce display methods, visualization devices, the advantages of printed versions, and the development of Korean versions. In terms of the 'Create built number' function, suggestions have been made to improve usability in terms of basic number selection, composite route guidance and error message provision, new reference and route construction, screen and button design, and built-number component guidance.

• Journal of information and communication convergence engineering
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• v.15 no.3
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• pp.170-174
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• 2017

Nowadays, people share and discuss scientific papers on social media such as the Web 2.0, big data, online forums, blogs, Twitter, Facebook and scholar community, etc. In addition to a variety of metrics such as numbers of citation, download, recommendation, etc., paper review text is also one of the effective resources for the study of scientific impact. The social media tools improve the research process: recording a series online scholarly behaviors. This paper aims to research the huge amount of paper reviews which have generated in the social media platforms to explore the implicit information about research papers. We implemented and shown the result of text mining on review texts using R language. And we found that Zika virus was the research hotspot and association research methods were widely used in 2016. We also mined the news review about one paper and derived the public opinion.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.735-736
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• 2009

사용자의 참여를 강조하는 Web2.0 시대를 맞이하여 개인의 블로그나 까페에 올라오는 무수히 많은 리뷰들이 실제 소비자의 마음을 움직이는 데에 많은 영향을 미치고 있다. 하지만 많은 리뷰들이 상당히 길게 작성되어 있기 때문에 원하는 정보만을 찾아내는 것은 어려운 일이다. 본 논문에서는 다양한 종류의 리뷰들 중에서도 많은 부분을 차지하고 있는 음식점에 관한 리뷰들을 분석하여 사용자가 원하는 정보를 요약하여 제공하는 방법을 제안한다. 이러한 방법을 통해서 사용자는 객관적인 판단을 내릴 수 있고, 시간적인 측면에서의 효율성을 획득할 수 있을 것이다.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.143-156
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• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.

• Journal of the Korea Computer Industry Society
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• v.2 no.11
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• pp.1445-1452
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• 2001

Internet system is now essential part of modern human life to get useful information totally by network. Moreover, in terms of travel agency business, the application of electronic commerce system using Internet is extremely important, because that providing and getting proper information is the focus to success in the business. They don't provide enough sub tools like keyboard searching function, sitemap and real-online reservation system. The bulletin board usually has a big role to gather visitors opinion, provide new information and Promotion their company to everyone.